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For Companies At a Glance
- Tasks: Build and scale data platforms for cutting-edge AI models on large datasets.
- Company: Well-funded AI company with a focus on innovative technology.
- Benefits: Competitive salary, growth opportunities, and a chance to work with industry leaders.
- Other info: Exciting growth potential with significant funding and collaboration with applied research teams.
- Why this job: Join a small, senior team and make a real impact in the AI field.
- Qualifications: Experience in deploying models, strong Python skills, and a product mindset.
The predicted salary is between 70000 - 90000 ÂŁ per year.
We’re working with an AI company building production‑grade systems for training and deploying cutting‑edge models on large‑scale multimodal data (video, embeddings, metadata). You’ll join a small, senior team owning the full ML lifecycle from data ingestion through to production inference, working closely with applied scientists on real‑world deployments.
What You’ll Do
- Build and scale data platforms for large multimodal datasets
- Improve ML training infrastructure using PyTorch and Ray
- Develop tooling for evaluation, experimentation, and dataset inspection
- Own model lifecycle systems from versioning to production rollout
What They’re Looking For
- Experience deploying models into production environments
- Strong Python plus a production language (e.g. C++ or Java)
- Experience with distributed systems and large‑scale data
- Product mindset with ability to solve real‑world problems end‑to‑end
- Model serving and inference systems
- Work on AI deployed at real‑world scale with massive datasets
- Close collaboration with applied research teams
- High ownership in a small, senior team
- Strong commercial traction with major industry partners
- Significant growth ahead with upcoming funding
Machine Learning Engineer - Staff/Senior employer: Atarus
Contact Detail:
Atarus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Staff/Senior
✨Tip Number 1
Network like a pro! Reach out to people in the AI and machine learning space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving large-scale data or production models. This is your chance to demonstrate your expertise beyond what's on paper.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and any other languages you know. Practice coding challenges and be ready to discuss your past projects in detail—this is where you can really shine!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it gives you a better chance of being noticed by our hiring team.
We think you need these skills to ace Machine Learning Engineer - Staff/Senior
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with deploying models into production and working with large-scale data. We want to see how your skills align with the role, so don’t be shy about showcasing your Python and any other relevant languages you've used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about working with AI and how your past experiences have prepared you for this role. Be specific about your contributions to previous projects and how they relate to what we do at StudySmarter.
Showcase Your Projects: If you’ve worked on any interesting projects, especially those involving multimodal datasets or model serving, make sure to mention them. We love seeing real-world applications of your skills, so include links to your GitHub or any relevant portfolios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Atarus
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and any production languages like C++ or Java. Brush up on your experience with PyTorch and Ray, as they’ll likely ask you about your hands-on experience with these tools.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled real-world problems using machine learning. Think about projects where you’ve built or improved ML systems, and be ready to explain your thought process and the impact of your work.
✨Understand the Full ML Lifecycle
Since this role involves owning the full ML lifecycle, be prepared to talk about your experience with data ingestion, model versioning, and production rollout. Highlight any tools or processes you’ve implemented that improved efficiency or effectiveness in these areas.
✨Emphasise Collaboration
This position requires close collaboration with applied scientists, so be ready to discuss how you’ve worked in teams before. Share examples of how you’ve communicated complex ideas to non-technical stakeholders and contributed to a team-oriented environment.